Earlier named entity (NE) recognition approaches involved information extraction programs developed by the Defense Advanced Research Projects Agency (DARPA). In this regard, seven named entity categories were defined in the DARPA benchmarks, including the named entity categories of person, organization, location, time, date, money, and percent. Other researchers continued this direction of work but with only the four named entity types of person, organization, location, and misc (See, e.g., Erik F. Tjong Kim Sang and Fien De Meulder, Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition, Proceedings of CoNLL-2003, Edmonton, 2003). While these named entity categories may be useful in certain applications, other named categories may be useful as well, including, for example, such named entity categories as product names, book names, song names, etc. Also, people do not always spell out names fully. In spoken language dialog applications, for example, partial names may be used to refer to their corresponding entities when the names are long. In contrast with the full name recognition, much less attention has been given to the task of partial name recognition.
Past work in the field of proper name recognition may have been focused on less complicated proper names, i.e., names without internal structure. Song and album names, and possibly other names such as book titles, may pose a special challenge to the recognition task. Researchers have tried to use proper name lists/databases to improve the performance of their methods. However, the results were mixed, with some reporting small improvement in certain instances (Andrei Mikheev, Claire Grover, and Marc Moens, Description of the LTG System Used for MUC-7, Proceedings of MUC-7, 1998), while others reported degradation in performance (Iris Hendrickx and Antal van den Bosch, Memory-based one-step named-entity recognition: Effects of seed list features, classifier stacking, and unannotated data, Proceedings of CoNLL-2003, Edmonton, Canada 2003; Dien De Meulder and Walter Daelemans, Memory-based Named Entity Recognition using Unannotated Data, Proceedings of CoNLL-2003, Edmonton, Canada 2003).